deeppapernote

DeepPaperNote

Use this skill when the user wants one outcome:

• read one paper carefully
• generate a high-quality Markdown note
• save the note into an Obsidian-style vault when configured, or into the current workspace when no vault is configured

Chinese trigger examples:

• 给这篇论文生成深度笔记
• 写一篇高质量论文精读笔记
• 把这篇文章整理成 obsidian 笔记
• 读这篇论文并生成 md 笔记

This skill is intentionally narrow:

• it handles one paper at a time
• it does not update daily reading lists
• it does not treat a shallow abstract rewrite as a successful output
• it does not split the public entrypoint into separate setup, troubleshooting, or start commands

Core Standard

The finished note must be more than a summary. It should reconstruct the paper's argument:

• what problem it solves
• how the task is defined
• what data or materials it uses
• how the method or analysis actually works
• what results matter most
• what the paper does not prove
• why the paper is worth keeping

Default writer persona:

• a top-tier researcher or algorithm engineer
• writing a replication-oriented lab note
• not writing a popular-science explanation
• assuming the reader can follow Python, PyTorch, training loops, and evaluation logic

The note must adapt to the paper type. Use the same base structure, but shift emphasis for AI methods, benchmarks, clinical studies, and humanities or social-science papers.

Workflow

Follow this order:

1. resolve the paper identity
2. collect metadata
3. acquire the best available PDF
4. extract canonical raw source text: *_raw_sections.jsonl, *_source_manifest.json, and optional derived *_full_text.md
5. extract structural indexes and PDF assets
6. plan figure placement
7. build the full figure/table decision table
8. build the manifest synthesis bundle
9. have the model read the bundle plus raw sections and plan the note
10. run grounding lint on the note plan before drafting from it
11. have the model write the note
12. lint the final note — if the lint output contains passes_style_gate: false, apply the Style Gate Enforcement rule before advancing to step 13, 14, or 15
13. perform final_quality_review after lint passes
14. perform final_readability_review after the quality review passes
15. write into Obsidian